Evaluation of Summaries Based on Lexical Chains Using Information Retrieval Task

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  • MOCHIZUKI HAJIME
    School of Information Science, Japan Advanced Institute of Science and Technology
  • OKUMURA MANABU
    Precision and Intelligence Laboratory, Tokyo Institute of Technology

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  • 語い的連鎖に基づく要約の情報検索タスクを用いた評価
  • ゴイテキ レンサ ニ モトヅク ヨウヤク ノ ジョウホウ ケンサク タスク オ モチイタ ヒョウカ

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Abstract

The importance of the automatic summarization research is now increasing with the growing availability of on-line documents. In information retrieval systems, summaries can be used as the display of the retrieval results, in order for users to quickly and accurately judge the relevance of the documents which are returned as a result of the users'query. Here, rather than producing a generic summary, the summary that reflects the user's topic of interest expressed in the query would be considered as more suitable. This type of summary is often called‘query-biased summary’. In this paper, we show that our previously proposed passage extraction method based on lexical chains can be used to produce better query-biased summaries for information retrieval systems. To evaluate the effectiveness of our method, a task-based evaluation scheme is adopted. The results from the experiments support that querybiased summaries by lexical chains outperform others in the accuracy of subject's relevance judgments. Furthermore, to establish a better evaluation methodology, we also investigate and describe the problems that arise from the experimental design.

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